trabecular bone

Quibim is proud to introduce its new advanced methodolgy to assess bone quality and fracture risk: QTS (Quality of Trabecular Structure). The need for a reliable approach for the characterization of trabecular microarchitecture is evident, as conditions and diseases related to trabecular bone quality and structure are becoming a focal point of precision medicine. Millions of dollars are spent in bone fracture care and prevention, which in many cases represent a grave danger to the patient health. In this scenario, can we rely upon available methods to predict bone fractures? Regrettably, the answer is no. Or so it was. Before we introduce QTS in detail, let’s first review some of the available methods to evaluate fracture risk.

In an attempt to fill this void in the search of a reliable predictor, new imaging biomarkers that guarantee to provide the needed sensibility and specificity have been developed. Trabecular Bone Score (TBS®) by Medimaps is a fracture risk predictor using DEXA as a source. TBS® performs a gray level analysis (textures) on the DEXA images to determine bone integrity. But, is DEXA adequate for this task? Unlike regular XR, in which it’s possible to assess the trabecular structure, DEXA’s low radiation is not enough for trabeculae differentiation. In addition, DEXA (like XR) represents a 3D structure as a projection onto a plane, losing spatial information.

Other medical imaging modalities are much more adequate for bone analysis and the subsequent fracture risk evaluation. Thanks to advanced computing models, Quibim has developed a new imaging biomarker that uses either magnetic resonance (MR), computerized tomography (CT) or X-ray imaging for a detailed characterization of the trabecular structure. QTS (Quality of Trabecular Structure) by Quibim introduces several advantages over other analysis methods:

QTS Score comprises all this information in a single score for a rapid and accurate characterization of the bone structure.

This groundbreaking analysis method is already available at our cloud web platform: Quibim Precision. Below we detail how to analyze your study in a few simple steps.

Quibim Precision allows the upload of studies in Dicom format. The upload process is easy, intuitive and 100% secure, guaranteeing the patient confidentiality thanks to Quibim’s anonymization and encryption system. The whole process is performed without the need of installing any additional software. To start, click on the green “Upload Study” button to the right of the website.

The platform will then ask for Dicom studies selection. With Google Chrome, we can drag and drop the study folder directly to the dotted box. With any other browser, we need to select the Dicom files to be uploaded.

Once the Dicom folders have been selected, Quibim Precision allows the pre-visualization of the study to choose which sequences we wish to upload. In this case, we need a CT, an X-ray or a 3D T1 MR.

After the selection, the files will be anonymized and encrypted. Quibim Precision will ask for an encryption password before the upload process starts. The user needs to preserve this password, as it’s needed for patient traceability.

After the upload process is completed, we click on the “Analyze Study” button of the study we want to evaluate.

This will take us to the detailed view of the study, where we can perform all actions related to it. First of all, we will choose among all the available sequences the one to be analyzed and its Quibim standard name. In this case, the name of the sequence is “Linear Attenuation [1/cm] (3035)”, which corresponds to the standard name “High Resolution CT”.

Next, we open the embedded Dicom viewer by clicking on “View”. Thanks to this viewer we can draw the ROI that will be used for the analysis. The viewer allows drawing 3D ROIs, first drawing a 2D rectangular ROI, and then selecting the slices on which it should be replicated. Clicking on “Apply” and “Save and go back” will store the ROI and it will be used for the analysis.

Finally, we should choose which analysis method we’ll use among all the available apps in Quibim Precision. In this case we’ll click on the “Start Analysis” button of the “3D Bone microarchitecture – QTS Score” app. The analysis process will then start, and the user doesn’t need to perform any other action than checking the results.

The results of the analysis are available on the view of the study. Once the analysis is completed we can check them by clicking on the “View Study” button on the “Processed Biomarkers” section.

We can examine the 3D reconstruction images and the numeric results of the extracted imaging biomarkers on the results view. Furthermore, we can download them and the structured report in pdf format, which includes all the generated data in a compact, easy to read way.

All the benefits of QTS are just a few clicks away. Create an account on Quibim Precision and start offering a real added value with your imaging studies.

For years, the image processing experts have applied texture analysis methods to medical images in order to extract indicators of composition and heterogeneity of the regions analysed. Texture analysis is applied in many imaging fields such as brain, muscle, bone, oncology, lung parenchyma and so on. Therefore it seems to be evident that it is a cross-specialty technique that can be applied to medical images to enhance the qualitative information that is frequently appreciated with quantitative data about composition and heterogenity. The applications in the oncology field are specially promising, with some clear conclusions in the Radiology journal indicating that texture analysis provides a very good prognosis evaluation of rectal cancer patients survival.

In the last 8 years, a texture-derived biomarker called Trabecular Bone Score (TBS) has been increasingly applied to the evaluation of fracture risk in patients. The TBS is calculated from the texture analysis applied to the densitometry (DXA) acquisitions of the column and it has been published to be related to osteoporosis and complementary to FRAX® in the follow-up of Osteoporosis in a significant number of studies.

Nevertheless, the applicability of texture analysis to any field has to be carefully analysed. The gold standard for fracture risk assessment is to experimentally evaluate the mechanical resistance by laboratory tests and it has to be noted that a significant discrepancy exists between the TBS performance in assessing fracture risk and the evidence of mechanical resistance evaluation of bone, as stated in this study:

“its discriminative power in fracture studies remains incomprehensible because prior biomechanical tests found no correlation with vertebral strength. To verify this result possibly owing to an unrealistic setup and to cover a wide range of loading scenarios, the data from three previous biomechanical studies using different experimental settings were used. They involved the compressive failure of 62 human lumbar vertebrae loaded 1) via intervertebral discs to mimic the in vivo situation (“full vertebra”); 2) via the classical endplate embedding (“vertebral body”); or 3) via a ball joint to induce anterior wedge failure (“vertebral section”). High-resolution peripheral quantitative computed tomography (HR-pQCT) scans acquired from prior testing were used to simulate anterior-posterior DXA from which areal bone mineral density (aBMD) and the initial slope of the variogram (ISV), the early definition of TBS, were evaluated. Finally, the relation of aBMD and ISV with failure load (Fexp) and apparent failure stress (σexp) was assessed, and their relative contribution to a multilinear model was quantified via ANOVA. We found that, unlike aBMD, ISV did not significantly correlate with Fexp and σexp, except for the “vertebral body” case (r2 = 0.396, p = 0.028). Aside from the “vertebra section” setup where it explained only 6.4% of σexp (p = 0.037), it brought no significant improvement to aBMD. These results indicate that ISV, a replica of TBS, is a poor surrogate for vertebral strength no matter the testing setup, which supports the prior observations and raises a fortiori the question of the deterministic factors underlying the statistical relationship between TBS and vertebral fracture risk. Maquer, G., Lu, Y., Dall’Ara, E., Chevalier, Y., Krause, M., Yang, L., Eastell, R., Lippuner, K. and Zysset, P. K. (2016), The Initial Slope of the Variogram, Foundation of the Trabecular Bone Score, Is Not or Is Poorly Associated With Vertebral Strength. J Bone Miner Res, 31: 341–346. doi:10.1002/jbmr.2610″

In QUIBIM we believe that a “trabecular score” should only be named in this way when enough depiction of the microarchitecture is achieved by imaging methods, like the existing in X-rays, computed tomography (CT) with collimations for high spatial resolution, high spatial resolution peripheral quantitative computed tomoraphy (HR-pQCT) or high spatial resolution magnetic resonance imaging (MRI). Trabeculae depiction can not be achieved with current DXA acquisitions, therefore we propose to name the TBS process simply by DXA texture analysis in order to avoid confusion.

Our computational algorithms allow for the quantitative characterization of trabecular bone properties from high spatial resolution imaging methods, including plain radiographs, therefore at similar dose and cost than current DXA. A complete structured report with the most important morphometry characteristics (Bone Volume to Total Volume – BV/TV; Trabecular thickness – Tb.Th; Trabecular Separation – Tb.Sp; Trabecular Number – Tb.N), irregularity indicators (Fractal Dimension in 2D and 3D – D2D, D3D) and mechanical analysis by the finite element method to calculate the Young’s modulus (Eapp). These methods have been validated against gold standards and high spatial resolution techniques. All these parameters are fused into a Trabecular Bone Architecture Quality Index to stratify fracture risk in patients. An intuitive structured report is generated for the clinician that allows to follow-up patients not only under clinical routine but also in the frame of clinical trials for the therapy response evaluation.

We have established the following plug-ins and methods for the assessment of Osteoporosis and bone diseases: